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The incorporation of LiDAR technology into some high-end smartphones hasunlocked numerous possibilities across various applications, includingphotography, image restoration, augmented reality, and more. In this paper, weintroduce a novel direction that harnesses LiDAR depth maps to enhance thecompression of the corresponding RGB camera images. Specifically, we propose aTransformer-based learned image compression system capable of achievingvariable-rate compression using a single model while utilizing the LiDAR depthmap as supplementary information for both the encoding and decoding processes.Experimental results demonstrate that integrating LiDAR yields an average PSNRgain of 0.83 dB and an average bitrate reduction of 16% as compared to itsabsence.

LiDAR Depth Map Guided Image Compression Model